class_docstr: Multiply the audio by a random amplitude factor to reduce or increase the volume. This
  technique can help a model become somewhat invariant to the overall gain of the input audio.
  
  Warning: This transform can return samples outside the [-1, 1] range, which may lead to
  clipping or wrap distortion, depending on what you do with the audio in a later stage.
  See also https://en.wikipedia.org/wiki/Clipping_(audio)#Digital_clipping
code: def randomize_parameters(
      self, samples: NDArray[np.float32], sample_rate: int
  ):
      super().randomize_parameters(samples, sample_rate)
      if self.parameters["should_apply"]:
          self.parameters[
              "amplitude_ratio"
          ] = convert_decibels_to_amplitude_ratio(
              random.uniform(self.min_gain_db, self.max_gain_db)
          )
  
file_path: audiomentations/audiomentations/augmentations/gain.py
imports: import random
  import warnings
  import numpy
  from numpy.typing import NDArray
  from audiomentations.core.transforms_interface import BaseWaveformTransform
  from audiomentations.core.utils import convert_decibels_to_amplitude_ratio
label_desc: Use image node_id 2 for calling the Gain obj's underlying member method code with example usage: obj.randomize_parameters(samples, sample_rate) without return types